Simulation from dependence models

Description

Simulate Monte Carlo sample from a collection of fitted conditional dependence models.

Usage

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mexMonteCarlo(nSample,mexList,mult=10)

Arguments

nSample

Required sample size.

mexList

List of fitted dependence models (returned by mexAll).

mult

Integer specifying what multiple of the total number of points should be generated for rejection sample

Details

Generates a Monte Carlo sample of the required size from a collection of conditional multivariate extreme values model of Heffernan and Tawn, 2004. For each marginal variable, the model that conditions on that margin is used to simulate values in the part of the sample space for which that margin is the largest of all marignal variables (measured on a quantile scale).

Value

A list with the following components:

nR

For each margin, number of original Monte Carlo points replaced by points generated under the corresponding conditional model.

MCsample

Matrix contiaining the Monte Carlo sample, dimension nSample by dimension of original dataset.

whichMax

Vector of indices indicating which variable is largest (on the quantile scale)

whichMaxAboveThresh

Logical vector indicating which of the variables identified by whichMax are additionally above the corresponding threshold for dependence estimation.

Author(s)

Harry Southworth, Janet E. Heffernan

References

J. E. Heffernan and J. A. Tawn, A conditional approach for multivariate extreme values, Journal of the Royal Statistical society B, 66, 497 – 546, 2004

Examples

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#  mAll <- mexAll(winter,mqu=0.7,dqu=c(0.7,0.7,0.7,0.7,0.7))
#  mexMC <- mexMonteCarlo(5000,mAll)
#  pairs(mexMC$MCsample)
  

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